Emma Skarstein

BIO

I’m a PhD student of statistics at the Norwegian University of Science and Technology (NTNU). I’m currently working with Bayesian methods for measurement error correction, using integrated nested Laplace approximation (INLA). Apart from that, I also really enjoy data visualization, specifically I use R programming language and the ggplot2 package for this.

PORTFOLIO

A selection of personal and professional work, including data visualizations, conference posters, presentation slides, and educational resources.

Research

We show how to handle missing data in INLA by generalizing existing measurement error models | Poster presentation from ISBA 2022 World meeting, presenting a method for covariate imputation in INLA using measurement error models. The poster received a prize.

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A JOINT BAYESIAN FRAMEWORK FOR MEASUREMENT ERROR AND MISSING DATA | Poster presentation from Nordstat 2021 conference, “The 28th Nordic Conference in Mathematical Statistics”, presenting my work on jointly modelling measurement error and missing data using INLA.

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Data graphics and visualization resources

TIDY TUESDAY DATA VISUALIZATIONS | Every Tuesday, the Tidy Tuesday project publishes a dataset for people to practice their data cleaning and data visualization. This GitHub repository contains all my contributions!

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CREATING CUSTOM THEMES IN GGPLOT2 | A cheatsheet created based on a presentation held for the NTNU statistics group coding group: “Moving beyond theme_gray: Exploring customized themes for improved visualizations in ggplot2”

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THE ANATOMY OF A GGPLOT2-PLOT | My reference for remembering all the different theme-variables in ggplot2.

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Emma Skarstein

BIO

I’m a PhD student of statistics at the Norwegian University of Science and Technology (NTNU). I’m currently working with Bayesian methods for measurement error correction, using integrated nested Laplace approximation (INLA). Apart from that, I also really enjoy data visualization, specifically I use R programming language and the ggplot2 package for this.

PORTFOLIO

A selection of personal and professional work, including data visualizations, conference posters, presentation slides, and educational resources.

Research

We show how to handle missing data in INLA by generalizing existing measurement error models | Poster presentation from ISBA 2022 World meeting, presenting a method for covariate imputation in INLA using measurement error models. The poster received a prize.

.

.

.

.

A JOINT BAYESIAN FRAMEWORK FOR MEASUREMENT ERROR AND MISSING DATA | Poster presentation from Nordstat 2021 conference, “The 28th Nordic Conference in Mathematical Statistics”, presenting my work on jointly modelling measurement error and missing data using INLA.

.

.

.

Data graphics and visualization resources

TIDY TUESDAY DATA VISUALIZATIONS | Every Tuesday, the Tidy Tuesday project publishes a dataset for people to practice their data cleaning and data visualization. This GitHub repository contains all my contributions!

.

.

.

CREATING CUSTOM THEMES IN GGPLOT2 | A cheatsheet created based on a presentation held for the NTNU statistics group coding group: “Moving beyond theme_gray: Exploring customized themes for improved visualizations in ggplot2”

.

.

THE ANATOMY OF A GGPLOT2-PLOT | My reference for remembering all the different theme-variables in ggplot2.

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